Systems and methods for detecting atrial tachyarrhythmia using heart sounds

ABSTRACT

Systems and methods for detecting atrial tachyarrhythmias (AT) such as atrial fibrillation (AF) are disclosed. A medical system can include a cardiac signal sensor circuit to sense a cardiac electrical signal and a heart sound (HS) sensor to sense heart a HS signal A cardiac electrical signal metric, including a cycle length variability or a detection of atrial electrical activity, can be generated from the cardiac electrical signal A HS metric can be generated from the HS signal, including a status of detection of S4 heart sound or a S4 heart sound intensity indicator. The system can include an AT detector circuit that can detect an AT event, such as an AF event, using the cardiac electrical signal metric and the HS metric The system can additionally classify the detected AT event as an AF or an atrial flutter event.

CLAIM OF PRIORITY

This application is a continuation of U.S. application Ser. No.15/335,873, filed Oct. 27, 2016, which claims the benefit of priorityunder 35 U.S.C. § 119(e) of U.S. Provisional Patent Application Ser. No.62/248,004, filed on Oct. 29, 2015, which is herein incorporated byreference in its entirety.

TECHNICAL FIELD

This document relates generally to medical devices, and moreparticularly, to systems, devices and methods for detecting atrialtachyarrhythmia using heart sounds.

BACKGROUND

Cardiac arrhythmia is an abnormality in the timing or pattern of theheartbeat. Atrial tachyarrhythmia is a cardiac arrhythmia characterizedby abnormally fast atrial rate, and can include various types ofarrhythmias including atrial fibrillation, atrial flutter, atrialtachycardia, supraventricular tachycardia, among others. Atrialfibrillation (AF) is the most common clinical arrhythmia, and accountsfor approximately one third of admissions resulting from cardiac rhythmdisturbances. During AF, the normal regular sinus rhythm is overwhelmedby disorganized electrical pulses originated from regions in or near anatrium. This can lead to irregular conductions to ventricles, causinginappropriately fast and irregular heart rate. One type of AF isparoxysmal AF which may last from minutes to days before it stops byitself. Another type known as persistent AF may last for over a week andtypically requires medication or other treatment to revert to normalsinus rhythm. The third type, permanent AF, is a condition where anormal heart rhythm cannot be restored with treatment. Persistent AF canbecome more frequent and result in permanent AF.

Congestive heart failure (CHF or HF) is another major cardiovascularepidemic and affects many people in the United. States alone. CHF is theloss of pumping power of the heart, resulting in the inability todeliver enough blood to meet the demands of peripheral tissues. CHFpatients typically have enlarged heart with weakened cardiac muscles,resulting in reduced contractility and poor cardiac output of blood. CHFcan affect the left heart, right heart or both sides of the heart,resulting in non-simultaneous contractions of the left ventricle andcontractions of the right ventricle. Such non-simultaneous contractions,also known as dyssynchroncy between the left and right ventricles, canfurther decrease the pumping efficiency of the heart.

There is a close pathophysiological relationship between AF and CHF. Alarge percentage of CHF patients may experience AF or other types ofatrial tachyarrhythmias. AF may facilitate the development orprogression of CHF, and CHF can increase the risk for the development ofAF. The prevalence of AF in patients with CHF increased in parallel withthe severity of CHF.

Overview

Atrial tachyarrrhthmias (AT), such as AF, can coexist with HF in manyCHF patients. AF may facilitate the development or progression of CHF inseveral ways. For example, during AF, irregularity of the ventricularcontractions can result in reduction in left ventricular (LV) fillingduring short cycles which is not completely compensated for by increasedfilling during longer cycles. The loss of effective atrial contractilefunction also contributes to the deterioration of LV filling,particularly in CHF patients with diastolic dysfunction. Presence ofuntreated or uncontrolled AF may also reduce effectiveness of CHFtherapies.

Timely and reliable detection of AF is necessary for treatment of AF andprevention of its exacerbating effect on CHF. Patients with AFfrequently experience inappropriately rapid heart rate and irregularventricular rhythm due to the loss of normal AV synchrony. As such,detection of an AF episode can be usually based on the fast atrial rate,or irregular ventricular contractions. However, atrial activity signalsuch as P wave in an electrocardiogram (ECG) can be a relatively weaksignal compared to ventricular activity such as R wave or QRS complexwhich is produced by ventricular depolarization. Atrial activity signalscan also be contaminated by noise, or interfered by various physiologicor environmental conditions. Although a dedicated atrial sensing such asby using an implanted lead placed in or near the atrium can improveatrial signal quality, it is not applicable to patient not indicated foratrial lead implantation. On the other hand, AF detection based onirregular ventricular contractions may suffer from confounding factorssuch as ventricular ectopic contracts or improper sensing of ventricularcontractions, which may also manifest irregularity in R waves or QRScomplexes. This can lead to reduced reliability of the detectedventricular contraction variability and false positive or false negativedetections of AF. Therefore, the present inventors have recognized thatthere remains a considerable need of systems and methods that canreliably and accurately detect an AF episode.

Ambulatory medical devices (AMDs) can be used for monitoring HF patientand detecting HF worsening events. Examples of such ambulatory medicaldevices can include implantable medical devices (IMDs), subcutaneousmedical devices, wearable medical devices or other external medicaldevices. Some AMDs can include a physiologic sensor that providesdiagnostic features. One type of such physiologic sensor is a sensor forsensing heart sounds. Heart sounds are associated with mechanicalvibrations from activity of a patient's heart and the flow of bloodthrough the heart. Heart sounds recur with each cardiac cycle and areseparated and classified according to the activity associated with thevibration. The first heart sound (S1) is associated with the vibrationalsound made by the heart during tensing of the mitral valve. The secondheart sound (S2) marks the beginning of diastole. The third heart sound(S3) can be related to filling pressures of the left ventricle duringdiastole. The fourth heart sound (S4) is associated with atrialcontraction. The present inventors have recognized that, because atrialcontraction may become diminished or irregular during an AF episode, aproperly detected heart sound signal, such as S4 heart sound, can beused to improve the accuracy and reliability of detecting an AF episode.

Various embodiments described herein can help improve detection of anatrial tachyarrhythmia such as an AF episode, or improve the process ofidentifying patients at elevated risk of developing an AF episode. Forexample, a medical system can include a cardiac signal sensor circuit tosense a cardiac electrical signal and a heart sound (HS) sensor to senseheart a HS signal. A cardiac electrical signal metric, including a cyclelength variability or a detection of atrial electrical activity, can begenerated from the cardiac electrical signal A HS metric can begenerated from the HS signal, including a status of detection of S4heart sound or a S4 heart sound intensity indicator. The system caninclude an AT detector circuit that can detect an AF event using thecardiac electrical signal metric and the HS metric.

In Example 1, a system can comprise a first sensor circuit and a secondsensor circuit, a memory circuit, a first signal metric generatorcircuit, a second signal metric generator circuit, and an atrialtachyarrhythmia (AT) detector circuit. The first sensor circuit caninclude a sense amplifier circuit to sense a cardiac electrical signalof a patient, and the second sensor circuit can include a senseamplifier circuit to sense a heart sound (HS) signal of the patient. Thefirst signal metric generator circuit can be coupled to the first sensorcircuit and the memory circuit to detect from the cardiac electricalsignal at least one signal component, and generate a cardiac electricalsignal metric using the at least one signal component. The cardiacelectrical signal metric can be stored in the memory circuit andindicative or correlative of atrial electrical activity. The secondsignal metric generator circuit can be coupled to the second signalsensor circuit and the memory circuit to detect from the HS signal atleast one HIS component including S4 heart sound, and generate a HISmetric using the at least one HS component. The HS metric can be storedin the memory circuit and indicative or correlative of atrial mechanicalcontraction. The AT detector circuit can be communicatively coupled tothe first and second signal metric generator circuits to detect an ATevent using the cardiac electrical signal metric and the HS metric.

Example 2 can include, or can optionally be combined with the subjectmatter of Example 1 to optionally include, the AT detector circuitconfigured to detect an atrial fibrillation (AF) event. The first signalmetric generator circuit can determine a cardiac cycle length (CL) or aheart rate (HR) from the cardiac electrical signal, and generate thecardiac electrical signal metric including a cycle length variability(CLV) of the CL or HR. The first signal metric can additionally oralternatively detect an atrial electrical activation from the cardiacelectrical signal, and generate the cardiac electrical signal metricincluding an amplitude of the detected atrial electrical activation. Thesecond signal metric generator circuit can detect the S4 heart soundwithin a cardiac cycle, and generate a S4 detection status indicatingwhether a S4 heart sound is detected within the cardiac cycle, or an S4intensity indicator indicative of intensity of the detected S4 heartsound.

Example 3 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include a first comparator circuit, asecond comparator circuit and a blending circuit. The first comparatorcircuit can compare the CLV value to a CLV threshold (CLV_(TH)). Thesecond comparator circuit can compare the S4 intensity indicator of thedetected S4 heart sound to a S4 intensity threshold (∥S4∥_(TH)). Theblending circuit can detect the AF event if (1) the CLV value exceedsthe CLV_(TH), and (2) the S4 detection status indicates a non-detectionof S4 heart sound, or the S4 intensity indicator falls below the∥S4∥_(TH).

Example 4 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include a first counter circuit, asecond counter circuit, and a blending circuit. The first countercircuit can determine a first relative number of a first subset of aplurality of CLV values computed over a plurality of cardiac cycles.Each CLV within the first subset exceeds a CLV threshold (CLV_(TH)). Thesecond counter circuit can determine a second relative number of asecond subset of the plurality of cardiac cycles. Each cardiac cyclewithin the second subset includes a detected S4 heart sound with acorresponding S4 intensity indicator exceeding a S4 intensity threshold(∥S4∥_(TH)). The blending circuit can generate a composite score usingthe first and second relative numbers, and detect the AF event if thecomposite score meets a specified criterion.

Example 5 can include, or can optionally be combined with the subjectmatter of Example 4 to optionally include, the blending circuit that cangenerate the composite score including a difference between the firstrelative number and the second relative number.

Example 6 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include, a beat selector circuitcoupled to the second signal metric generator circuit. The beat selectorcircuit can select, from a plurality of cardiac cycles for detecting S4heart sound, a subset of cardiac cycles each having the S4 detectionstatus indicating non-detection of S4 heart sound within thecorresponding cardiac cycle, or the S4 intensity indicator falling belowa S4 intensity threshold. The first signal metric generator circuit canto compute the CLV value using the selected subset of the cardiaccycles. The AT detector circuit can detect the AF event if the CLV valueexceeds a CLV threshold.

Example 7 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include, a beat selector circuitcoupled to the first signal metric generator circuit. The beat selectorcircuit can select from a plurality of cardiac cycles a subset ofcardiac cycles corresponding to the CLV exceeding a CLV threshold. Thesecond signal metric generator circuit is configured to detect S4 heartsounds within the selected subset of the cardiac cycles and generate aS4 detection status. The AT detector circuit can detect the AF event ifthe S4 detection status indicating non-detection of S4 heart soundwithin the selected subset of the cardiac cycles, or the S4 intensityindicator falling below a S4 intensity threshold.

Example 8 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include, an activity sensor circuitthat can detect a physical activity level of the patient. The ATdetector circuit can detect the AF event using the detected atrialelectrical activation if the detected physical activity level exceeds aspecified activity threshold, or detect the AF event using the detectedS4 heart sound if the detected physical activity level falls below thespecified activity threshold.

Example 9 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include, a posture sensor circuit thatcan detect a posture of the patient. The AT detector circuit can detectthe AF event using the detected atrial electrical activation if thedetected posture is a first posture, or detect the AF event using thedetected S4 heart sound if the detected posture is a different secondposture.

Example 10 can include, or can optionally be combined with the subjectmatter of Example 2 to optionally include, the first signal metricgenerator circuit that can detect from the cardiac electrical signal theatrial electrical activation and the CL or the HR, and generate thecardiac electrical signal metric including the CLV. The AT detectorcircuit can detect the AF event if the CLV value exceeds a CLV threshold(CLV_(TH)). The CLV_(TH) can be determined using one or both of thedetection of the S4 heart sound and the detection of the atrialelectrical activation.

Example 11 can include, or can optionally be combined with the subjectmatter of Example 10 to optionally include, the AT detector circuit thatcan determine a first CLV threshold (CLV_(TH1)in response to both of adetection of S4 heart sound and a detection of atrial electricalactivation, a second CLV threshold (CLV_(TH2)) in response to one of adetection of S4 heart sound or a detection of atrial electricalactivation, or a third CLV threshold (CLV_(TH3)) in response to neithera detection of S4 heart sound nor a detection of atrial electricalactivation. The threshold CLV_(TH1) can be greater than the CLV_(TH2),and the CLV_(TH2) can be greater than the CLV_(TH3).

Example 12 can include, or can optionally be combined with the subjectmatter of Example 10 to optionally include, the AT detector circuit thancan determine a first CLV threshold (CLV_(TH1)) in response to thedetection of S4 heart sound, a second CLV threshold (CLV_(TH2)) inresponse to the detection of atrial electrical activation, or a thirdCLV threshold (CLV_(TH3)) in response to neither a detection of S4 heartsound nor a detection of atrial electrical activation. The thresholdCLV_(TH1) can be different from the CLV_(TH2), and the CLV_(TH3) can beless than CLV_(TH1) and less than CLV^(TH2).

Example 13 can include, or can optionally be combined with the subjectmatter of one or any combination of Examples 1 through 12 to include, anarrhythmia classifier circuit coupled to the memory circuit or the firstand second signal metric generator circuits. The arrhythmia classifiercircuit can determine a composite metric using the cardiac electricalsignal metric and the HS metric, and confirm the detected. AT event asan AF event if the composite metric meets a first specified criterion,or classify the detected AT event as an atrial flutter (AFL) event ifthe composite metric meets a second specified criterion.

Example 14 can include, or can optionally be combined with the subjectmatter of Example 13 to optionally include, the composite metricincluding a variability (AVR_(var)) of an actio-ventricular conductionpattern including a ratio (AVR) of a number of S4 heart sounds to anumber of ventricular activations during a specified number of cardiaccycles. The arrhythmia classifier circuit can confirm the detected ATevent as an AF event if the AVR_(var) exceeds a specified threshold, orclassify the detected AT event as an AFL event if the AVR_(var) fallsbelow the specified threshold.

Example 15 can include, or can optionally be combined with the subjectmatter of Example 13 to optionally include, the composite metricincluding a variability (AVI_(var)) of atrio-ventricular intervalincluding an interval between the detected S4 heart sound and theventricular activation within the same cardiac cycle. The arrhythmiaclassifier circuit can confirm the detected AT event as an AF event ifthe AVI_(var) exceeds a specified threshold, or classify the detected ATevent as an AFL event if the AVI_(var) falls below the specifiedthreshold.

In Example 16, a method can include steps of sensing a cardiacelectrical signal of a patient, generating from the sensed cardiacelectrical signal a cardiac electrical signal metric indicative orcorrelative of atrial electrical activity, sensing a heart sound (HS)signal of the patient, generating from the sensed HS signal a HS metricindicative or correlative of atrial mechanical contraction, the HSmetric including a S4 heart sound metric, and detecting an atrialtachyarrhythmia (AT) event using the cardiac electrical signal metricand the HS metric.

Example 17 can include, or can optionally be combined with the subjectmatter of Example 16 to optionally include, generating the cardiacelectrical signal metric including one or more of a cycle lengthvariability (CLV) of cycle length (CL) or HR computed from the cardiacelectrical signal or an atrial electrical activation detected from thecardiac electrical signal, and generating the HS metric including one ormore of a S4 detection status indicating whether a S4 heart sound isdetected within the cardiac cycle, or a S4 intensity indicator of thedetected S4 heart sound. Example 17 can include detecting the AT eventincludes detecting an atrial fibrillation (AF) event if (1) the CLVvalue exceeds a CLV threshold (CLV_(TH)), and (2) the S4 detectionstatus indicates a non-detection of S4 heart sound, or the S4 intensityindicator falls below a S4 intensity threshold (∥S4∥_(TH)).

Example 18 can include, or can optionally be combined with the subjectmatter of Example 17 to optionally include, determining a first relativenumber of a first subset of a plurality of CLV values computed over aplurality of cardiac cycles, each CLV within the first subset exceedingthe CLV_(TH), and a second relative number of a second subset of theplurality of cardiac cycles each including a detected S4 heart soundwith a corresponding S4 intensity indicator exceeding the ∥S4∥_(TH).Example 18 can including generating a composite score using the firstand second relative numbers, and detecting the AF event if the compositescore meets a specified criterion.

Example 19 can include, or can optionally be combined with the subjectmatter of Example 17 to optionally include, selecting from a pluralityof cardiac cycles for detecting S4 heart sound a subset of cardiaccycles each having the S4 detection status indicating non-detection ofS4 heart sound within the corresponding cardiac cycle, or the S4intensity indicator falling below the ∥S4∥_(TH). Example 19 can includegenerating the CLV value using the selected subset of the cardiaccycles, and detecting the AF event if the CLV value exceeds theCLV_(TH).

Example 20 can include, or can optionally be combined with the subjectmatter of Example 17 to optionally include, detecting at least one of aphysical activity level or a posture of the patient, and detecting theAF event using the detected atrial electrical activation if the detectedphysical activity level exceeds a specified activity threshold or thedetected posture is a first posture, or detecting the AF event using thedetected. S4 heart sound if the detected physical activity level fallsbelow the specified activity threshold or the detected posture is adifferent second posture.

Example 21 can include, or can optionally be combined with the subjectmatter of Example 17 to optionally include, determining the CLV_(TH)using one or both of the detection of the S4 heart sound and thedetection of the atrial electrical activation. The CLV_(TH) can be afirst CLV threshold (CLV_(TH)) in response to both of a detection of S4heart sound and a detection of atrial electrical activation, a secondCLV threshold (CLV_(TH2)) in response to one of a detection of S4 heartsound or a detection of atrial electrical activation, or a third CLVthreshold (CLV_(TH3)) in response to neither a detection of S4 heartsound nor a detection of atrial electrical activation. The CLV_(TH1) canbe greater than the CLV_(TH2), and the CLV_(TH2) can be greater than theCLV_(TH3). Example 21 can include detecting the AF event if the CLVvalue exceeds the CLV_(TH).

Example 22 can include, or can optionally be combined with the subjectmatter of Example 16 to optionally include, classifying the detected ATevent as one of an atrial fibrillation (AF) event or an atrial flutter(AFL) event. A composite metric can be computed using the cardiacelectrical signal metric and the HS metric, the composite metric caninclude one of more of an atrio-ventricular conduction pattern or anatrio-ventricular interval. The classification can include confirmingthe detected AT event as an AF event if the composite metric meets afirst specified criterion indicating a consistent atrio-ventricularconduction pattern or a stable atrio-ventricular interval, orclassifying the detected AT event as an AFL, event if the compositemetric meets a second specified criterion indicating an inconsistentatrio-ventricular conduction pattern or an unstable atrio-ventricularinterval.

This Overview is an overview of some of the teachings of the presentapplication and not intended to be an exclusive or exhaustive treatmentof the present subject matter. Further details about the present subjectmatter are found in the detailed description and appended claims. Otheraspects of the invention will be apparent to persons skilled in the artupon reading and understanding the following detailed description andviewing the drawings that form a part thereof, each of which are not tobe taken in a limiting sense. The scope of the present invention isdefined by the appended claims and their legal equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments are illustrated by way of example in the figures ofthe accompanying drawings. Such embodiments are demonstrative and notintended to be exhaustive or exclusive embodiments of the presentsubject matter.

FIG. 1 illustrates generally an example of a cardiac rhythm management(CRM) system and portions of the environment in which the CRM systemoperates.

FIG. 2 illustrates generally an example of a HS-based atrialtachyarrhythmia (AT) detection circuit.

FIG. 3 illustrates generally another example of an AT detection circuit.

FIG. 4 illustrates generally an example of a method for detecting an ATevent in a patient.

FIGS. 5A-B illustrate generally examples of methods for detecting an AFevent using a cardiac electrical signal metric and a HS metric.

FIG. 6 illustrates generally an example of a method for detecting an AFevent using a cardiac electrical signal, a HS signal, and informationabout physical activity level of the patient.

FIG. 7 illustrates generally an example of a method for detecting an AFevent using a cardiac electrical signal, a HS signal, and postureinformation.

FIG. 8 illustrates generally another example of a method for detectingan AF event using a cardiac electrical signal and a HS signal.

DETAILED DESCRIPTION

Disclosed herein are systems, devices, and methods for detecting atrialtachyarrhythmias such as atrial fibrillation (AF). By monitoring apatient's cardiac electrical activity and a heart sound (HS) signal, thesystem and methods discussed in the present document can be used totimely and reliably detect an AF episode, thereby allowing immediatemedical attention to the patient. The systems and methods discussed inthis document can also be used for detecting other types of atrialtachyarrhythmias such atrial tachycardia, atrial flutter, orsupraventricular tachycardia.

FIG. 1 illustrates an example of a Cardiac Rhythm Management (CRM)system 100 and portions of an environment in which the CRM system 100can operate. The CRM system 100 can include an ambulatory medicaldevice, such as an implantable medical device (IMD) 110 that can beelectrically coupled to a heart 105 such as through one or more leads108A-C, and an external system 120 that can communicate with the IMD 110such as via a communication link 103. The IMD 110 may include animplantable cardiac device such as a pacemaker, an implantablecardioverter-defibrillator (ICD), or a cardiac resynchronization therapydefibrillator (CRT-D). The IMD 110 can include one or more monitoring ortherapeutic devices such as a subcutaneously implanted device, awearable external device, a neural stimulator, a drug delivery device, abiological therapy device, a diagnostic device, or one or more otherambulatory medical devices. The IMD 110 may be coupled to, or may besubstituted by a monitoring medical device such as a bedside or otherexternal monitor.

As illustrated in FIG. 1, the POD 110 can include a hermetically sealedcan 112 that can house an electronic circuit that can sense aphysiological signal in the heart 105 and can deliver one or moretherapeutic electrical pulses to a target region, such as in the heart,such as through one or more leads 108A-C. The CRM system 100 can includeonly one lead such as 108B, or can include two leads such as 108A and108B.

The lead 108A can include a proximal end that can be configured to beconnected to IMD 110 and a distal end that can be configured to beplaced at a target location such as in the right atrium (RA) 131 of theheart 105. The lead 108A can have a first pacing-sensing electrode 141that can be located at or near its distal end, and a secondpacing-sensing electrode 142 that can be located at or near theelectrode 141. The electrodes 141 and 142 can be electrically connectedto the IMD 110 such as via separate conductors in the lead 108A, such asto allow for sensing of the right atrial activity and optional deliveryof atrial pacing pulses. The lead 108B can be a defibrillation lead thatcan include a proximal end that can be connected to IMD 110 and a distalend that can be placed at a target location such as in the rightventricle (RV) 132 of heart 105. The lead 108B can have a firstpacing-sensing electrode 152 that can be located at distal end, a secondpacing-sensing electrode 153 that can be located near the electrode 152,a first defibrillation coil electrode 154 that can be located near theelectrode 153 and a second defibrillation coil electrode 15:5 that canbe located at a distance from the distal end such as for superior venacava (SVC) placement. The electrodes 152 through 155 can be electricallyconnected to the IMD 110 such as via separate conductors in the lead108B. The electrodes 152 and 153 can allow for sensing of a ventricularelectrogram and can optionally allow delivery of one or more ventricularpacing pulses, and electrodes 154 and 155 can allow for delivery of oneor more ventricular cardioversion/defibrillation pulses. In an example,the lead 108B can include only three electrodes 152, 154 and 155. Theelectrodes 152 and 154 can be used for sensing or delivery of one ormore ventricular pacing pulses, and the electrodes 154 and 155 can beused for delivery of one or more ventricular cardioversion ordefibrillation pulses. The lead 108C can include a proximal end that canbe connected to the IMD 110 and a distal end that can be configured tobe placed at a target location such as in a left ventricle (LV) 134 ofthe heart 105. The lead 108C may be implanted through the coronary sinus133 and may be placed in a coronary vein over the LV such as to allowfor delivery of one or more pacing pulses to the LV. The lead 1080 caninclude an electrode 161 that can be located at a distal end of the lead108C and another electrode 162 that can be located near the electrode161. The electrodes 161 and 162 can be electrically connected to the IMD110 such as via separate conductors in the lead 1080 such as to allowfor sensing of the LV electrogram and optionally allow delivery of oneor more resynchronization pacing pulses from the LV. Additionalelectrodes can be included in or along the lead 108C. In an example, asillustrated in FIG. 1, a third electrode 163 and a fourth electrode 164can be included in the lead 108. In some examples (not shown in FIG. 1),at least one of the leads 108A-C, or an additional lead other than theleads 108A-C, can be implanted under the skin surface without beingwithin at least one heart chamber, or at or close to heart tissue.

The IMD 110 can include an electronic circuit that can sense aphysiological signal. The physiological signal can include anelectrogram or a signal representing mechanical function of the heart105. The hermetically sealed can 112 may function as an electrode suchas for sensing or pulse delivery. For example, an electrode from one ormore of the leads 108A-C may be used together with the can 112 such asfor unipolar sensing of an electrogram or for delivering one or morepacing pulses. A defibrillation electrode from the lead 108B may be usedtogether with the can 112 such as for delivering one or morecardioversion defibrillation pulses. In an example, the IMD 110 cansense impedance such as between electrodes located on one or more of theleads 108A-C or the can 112. The IMD 110 can be configured to injectcurrent between a pair of electrodes, sense the resultant voltagebetween the same or different pair of electrodes, and determineimpedance using Ohm's Law. The impedance can be sensed in a bipolarconfiguration in which the same pair of electrodes can be used forinjecting current and sensing voltage, a tripolar configuration in whichthe pair of electrodes for current injection and the pair of electrodesfor voltage sensing can share a common electrode, or tetrapolarconfiguration in which the electrodes used for current injection can bedistinct from the electrodes used for voltage sensing. In an example,the IMD 110 can be configured to inject current between an electrode onthe RV lead 108B and the can housing 112, and to sense the resultantvoltage between the same electrodes or between a different electrode onthe RV lead 108B and the can housing 112. A physiologic signal can besensed from one or more physiological sensors that can be integratedwithin the IMD 110. The IMD 110 can also be configured to sense aphysiological signal from one or more external physiologic sensors orone or more external electrodes that can be coupled to the IMD 110.Examples of the physiological signal can include one or more ofelectrocardiogram, intracardiac electrogram, arrhythmia, heart rate,heart rate variability, intrathoracic impedance, intracardiac impedance,arterial pressure, pulmonary artery pressure, left atrial pressure, RVpressure, LV coronary pressure, blood temperature, blood oxygensaturation, one or more heart sounds, physical activity or exertionlevel, physiologic response to activity, posture, respiration, bodyweight, or body temperature.

The arrangement and functions of these leads and electrodes aredescribed above by way of example and not by way of limitation.Depending on the need of the patient and the capability of theimplantable device, other arrangements and uses of these leads andelectrodes are possible.

As illustrated, the CRM system 100 can include a heart sounds-basedatrial tachyarrhythmia (AT) event detection circuit 113. The heartsounds-based AT event detection circuit 113 can be configured to detecta heart sound (HS) signal such as by using an implantable sensor, andproduce a HS metric indicative or correlative of atrial mechanicalcontraction. The heart sounds-based AT event detection circuit 113 canadditionally detect a cardiac electrical signal and generate a signalmetric indicative or correlative of atrial electrical activity. Theheart sounds-based AT event detection circuit 113 can combine the signalmetrics indicative of atrial electrical activity and the signal metricsindicative of atrial mechanical contraction to detect an AT event, suchas a atrial fibrillation (AF) event. Examples of heart sounds-based ATevent detection circuit 113 are described below, such as with referenceto FIGS. 2-3.

The external system 120 can allow for programming of the IMD 110 and canreceive information about one or more signals acquired by IMD 110, suchas can be received via a communication link 103. The external system 120can include a local external IMD programmer. The external system 120 caninclude a remote patient management system that can monitor patientstatus or adjust one or more therapies such as from a remote location.

The communication link 103 can include one or more of an inductivetelemetry link, a radio-frequency telemetry link, or a telecommunicationlink, such as an internet connection. The communication link 103 canprovide for data transmission between the IMD 110 and the externalsystem 120. The transmitted data can include, for example, real-timephysiological data acquired by the IMD 110, physiological data acquiredby and stored in the IMD 110, therapy history data or data indicatingIMD operational status stored in the IMD 110, one or more programminginstructions to the IMD 110 such as to configure the IMD 110 to performone or more actions that can include physiological data acquisition suchas using programmably specifiable sensing electrodes and configuration,device self-diagnostic test, or delivery of one or more therapies.

The heart sounds-based AT event detection circuit 113 can be implementedat the external system 120 such as using data extracted from the IMD 110or data stored in a memory within the external system 120. Portions ofthe heart sounds-based AT event detection circuit 113 may be distributedbetween the IMD 110 and the external system 120.

Portions of the IMD 110 or the external system 120 can be implementedusing hardware, software, or any combination of hardware and software.Portions of the IMD 110 or the external system 120 may be implementedusing an application-specific circuit that can be constructed orconfigured to perform one or more particular functions, or can beimplemented using a general-purpose circuit that can be programmed orotherwise configured to perform one or more particular functions. Such ageneral-purpose circuit can include a microprocessor or a portionthereof, a microcontroller or a portion thereof, or a programmable logiccircuit, or a portion thereof. For example, a “comparator” can include,among other things, an electronic circuit comparator that can beconstructed to perform the specific function of a comparison between twosignals or the comparator can be implemented as a portion of ageneral-purpose circuit that can be driven by a code instructing aportion of the general-purpose circuit to perform a comparison betweenthe two signals.

While described with reference to the IMD 110, the CRM system 100 caninclude a subcutaneous medical device (e.g., subcutaneous pacemaker orICD, a subcutaneous monitor, or a subcutaneous diagnostic device), awearable medical device (e.g., a patch based sensing device), or otherexternal medical devices for medical diagnostics or therapy usingvarious energy sources (e.g., electrical, electromagnetic, optical, ormechanical) or therapeutic agents. The subcutaneous, wearable, orexternal medical device can be an untethered device that needs not betethered to an electrode or another device by a leadwire or other wiredconnection (such as one of the leads 108A-C). The untethered device caninclude one or more electrodes on a can housing of the device, orwirelessly communicate with a sensor or another device associated withthe patient.

FIG. 2 illustrates an example of a heart sound (HS)-based atrialtachyarrhythmia (AT) detection circuit 200, which can be an embodimentof the heart sounds-based AT event detection circuit 113. The HS-basedAT detection circuit 200 can alternatively be implemented in an externalsystem such as a patient monitor configured for providing diagnosticinformation to an end-user. The HS-based AT detection circuit 200 caninclude one or more of a cardiac electrical signal sensor circuit 210, aHS sensor circuit 220, a cardiac electrical signal metric generatorcircuit 212, a HS metric generator circuit 222, a memory circuit 230, anAT detector circuit 240, a controller circuit 250, and a user interfaceunit 250.

The cardiac electrical signal sensor circuit 210 can sense a cardiacelectrical signal from a patient. The cardiac electrical signal sensorcircuit 210 can include one or more implantable, wearable, or otherwiseambulatory cardiac activity sensors configured to sense cardiacelectrical activity. In an example, the cardiac activity sensor caninclude electrodes on one or more of the leads 108A-C or the can 112.The electrodes are configured for sensing one or more electrograms(EGMs) from inside the heart chamber, inside the heart tissue, on ornear the surface of the heart. The electrodes can be non-invasivelyattached to the skin to sense a surface electrocardiogram (ECG). Theelectrodes can also placed subcutaneously (e.g., under the skin) tosense a subcutaneous ECG.

The cardiac electrical signal sensor circuit 210 can include one or moreamplifiers, analog to digital converters, filters, or other signalconditioning circuits that can process the sensed cardiac electricalactivity, such as an ECG, a subcutaneous ECG, or an EGM. The cardiacelectrical signal sensor circuit 210 can detect from the processedcardiac electrical activity signals electrophysiological events such asevents indicative of depolarization or repolarization of a specifiedportion of the heart, such as an atrium, a ventricle, a His-bundle, or aseptum.

The cardiac electrical signal metric generator circuit 212 can becoupled to the cardiac electrical signal sensor circuit 210 to detectfrom the cardiac electrical signal at least one signal component, andgenerate a signal metric using the at least one signal component. In oneexample, the cardiac electrical signal sensor circuit 210 can senseventricular depolarizations such as R waves or QRS complexes from theECG signal, or ventricular sensing (Vs) events from the ventricular EGMsuch as by using at least one electrode on the RV lead 108B or the LVlead 108C, The cardiac electrical signal sensor circuit 210 can derivefrom the sensed ventricular depolarizations a heart rate (HR) or a cyclelength (CL) signal. The CL can be determined as, for example, intervalsbetween two adjacent R waves, and the HR can be computed using the CL.The cardiac electrical signal metric generator circuit 212 can generatethe cardiac electrical signal metric including a cycle lengthvariability (CLV) or a heart rate variability (HRV), which can berespectively computed as a spreadness measure over a plurality CLs orHRs. One example of the spreadness measure can include first-orderstatistics such as an average of beat-to-beat difference in HR or CLmeasurements, second-order statistics such as a variance or a standarddeviation, or higher-order statistics of the HR or CL measurements.Another example of the spreadness measure can include geometric featuresextracted from a two dimensional scatter plot between two successive HRor CL measurements (e.g., CL(n) vs. CL(n−1)) or from a higherdimensional scatter plot among three or more HR or CL measurements(e.g., CL(n) vs. CL(n−1) vs. CL(n−2)).

In another example, the cardiac electrical signal sensor circuit 210 cansense atrial electrical activity, such as P waves from the ECG or atrialsensing events acquired using at least one atrial electrode on theatrial lead 108A. The cardiac electrical signal metric generator circuit212 can generate the cardiac electrical signal metric including apresence or intensity of atrial depolarizations. The cardiac electricalsignal metric, such as the CLV, HRV, or the presence or intensity of theatrial depolarizations such as the P waves, can be stored in the memorycircuit 230.

The HS sensor circuit 220 can sense HS information indicative ofacoustic or mechanical activity of a heart. The HS information caninclude information of at least one HS component, such as S1, S2, S3, orS4 heart sound. In an example, the HS waveform can include at least oneensemble average of a HS signal over multiple physiological cycles suchas multiple cardiac cycles, or over a specified time period such as oneminute, ten minutes, one hour, one day, etc.

The HS sensor circuit 220 can be coupled to one or more physiologicsensors that can be configured to sense, detect, or otherwise obtain HSinformation from a subject. Such physiologic sensors, hereinafterreferred to as “HS sensors”, can be an implantable, wearable, orotherwise ambulatory sensor, and placed external to the patient orimplanted inside the body. Examples of the HS sensor can include anaccelerometer, an acoustic sensor, a microphone, a piezo-based sensor,or other vibrational or acoustic sensors can also be used to sense theHS signal. The HS sensor can be included in at least one part of animplantable system, such as an implantable medical device, or a leadcoupled to the implantable medical device. In an example, the signalsensor circuit 210 can be configured to receive the HS information froma device capable of collecting or storing the HS information. Examplesof such a device can include an external programmer, an electronicmedical record system, a memory unit, or other data storage devices.

The HS sensor circuit 220 can include a sense amplifier circuit that canpre-process a sensed HS signal, including amplification, digitization,filtering, or other signal conditioning operations. In an example, thesignal sensor circuit 210 can include a bandpass filter adapted tofilter the received HS signal to a frequency range of approximatelybetween 5 and 90 Hz, or approximately between 9 and 90 Hz. In anexample, the signal sensor circuit 210 can include a double orhigher-order differentiator configured to calculate a double orhigher-order differentiation of the received HS signal.

The HS metric generator circuit 222 can detect from the HS signal atleast one HS component, and generate a HS metric indicative orcorrelative of atrial mechanical contraction using the at least one HScomponent. In an example, the HS metric generator circuit 222 can detecta S4 heart sound, among other heart sound components. The S4 heart soundmay generally be associated with atrial contraction. During AF, regularand forceful atrial contraction may be diminished. As such, a detectionof forceful S4 can be an evidence of absence of AF. The HS metricgenerator circuit 222 can detect S4 using a specified detection window,such as with reference to a physiologic event such as R wave, Q wave, orQRS complexes obtained from an electrocardiogram or an intracardiacelectrogram signal synchronously sensed with the HS signal. The HSmetric generator circuit 222 can detect S4 heart sound along with one ormore other heart sounds such as S1, S2, or S3. In an example, because S4generally occurs temporally following S3 and prior to S1 of the nextcardiac cycle, the S4 detection window can be with reference to detectedS1 or S3 heart sound. The HS metric generator circuit 222 can calculateHS signal energy within the S4 detection window, and detects the S4 ifthe HS signal energy exceeds a specified threshold. In an example, theHS metric generator circuit 222 can detect the HS component adaptivelyby tracking the temporal locations of the previously detected HScomponent. Additionally or alternatively, the HS metric generatorcircuit 222 can detect S4 heart sound using a S4 template matchingmethod, A S4 morphological template can be created using the known S4signal portion extracted from the patient's HS signal. A matching score,such as a cross correlation, between a segment of HS signal within acardiac cycle and the S4 template can be computed. An S4 can be detectedif the matching score exceeds a threshold value.

The HS metric generator circuit 222 can generate one or more HS metricsincluding a detection status of S4 heart sound, and temporal,statistical, or morphological features of the detected S4 heart sound.Examples of the intensity of a HS component can include amplitude of adetected HS component in a time-domain HS signal, a transformed HSsignal such as integrated HS energy signal, or in a frequency-domain HSsignal such as the peak value of the power spectral density, or peakvalue of a generic measurement within the respective HS detectionwindow, such as peak envelop signal or root-mean-squared value of theportion of the HS signal within the HS detection window. The intensityof a HS component can also include a slope or rate of change of signalamplitude or peak energy. In an example, the HS metric can include anintensity measure of a portion of the HS signal that includes at least aportion of a specified HS component, such as a root-mean-squared valueof the HS signal portion between an R wave and a subsequent S1 heartsound, or between an R wave and a subsequent S2 heart sound, within thesame cardiac cycle. The HS metric, such as the detection of S4, orintensity or other features derived from the detected S4 heart sound,can be stored in the memory circuit 230.

The AT detector circuit 240 can be communicatively coupled to the memorycircuit 230, or the cardiac electrical signal metric generator circuit212 and the HS metric generator circuit 222. The AT detector circuit 240can use one or more of the cardiac electrical signal metrics or the HSmetrics to detect an AT event, such as an AF event. In an example, theAT detector circuit 240 can be implemented as a part of a microprocessorcircuit in the CRM system 100. The microprocessor circuit can be adedicated processor such as a digital signal processor, applicationspecific integrated circuit (ASIC), microprocessor, or other type ofprocessor for processing information including heart sounds.Alternatively, the microprocessor circuit can be a general purposeprocessor that can receive and execute a set of instructions ofperforming the functions, methods, or techniques described herein.

The AT detector circuit 240 can include a first comparator circuit 242,a second comparator circuit 244, and a blending circuit 246. The firstcomparator circuit 242 can compare the cardiac electrical signal metricto a specified criterion and produce an atrial rhythm indicator. In anexample, the first comparator circuit 242 can compare the CLV value to aCLV threshold (CLV_(TH)), and produce an atrial rhythm indicator if theCLV value exceeds the CLV_(TH). The second comparator circuit 244 cancompare the HS metric to a specified criterion and produce an atrialkick indicator. In an example, if an S4 is detected by the HS metricgenerator circuit 222, the second comparator circuit 244 can compare thedetected S4 intensity (∥S4∥) to a S4 intensity threshold (∥S4∥_(TH)),and produce the atrial kick indicator including an indication of anon-detection of S4 heart sound, or an indicator of the detected S4intensity exceeding or falling below the ∥S4∥_(TH).

The blending circuit 246 can combine the atrial rhythm indicator and theatrial kick indicator to detect an AF event. In an example, an AF eventis detected if (1) the CLV value exceeds the CLV_(TH), and (2) the S4heart sound is not detected, or the S4 intensity indicator falls belowthe ∥S4∥_(TH). In an example, the CLV_(TH) can be set a relatively lowlevel such that CLV can be sensitive to cycle length variations. The∥S4∥_(TH) can be selected such that the atrial kick indicator, such as anon-detection of S4 or a below-the-threshold S4 intensity, can bespecific to an AF event. In an example of using an accelerometer sensorto sense HS and detecting HS components (e.g., S4 heart sound) fromroot-mean-squared (RMS) values of the acceleration signal, the ∥S4∥_(TH)can be approximately 0.6 milli-G, as a non-limiting example.

In some examples, the first comparator circuit 242 can compare the CLVvalue to a distribution of CLV values to determine a first likelihoodvalue of the CLV value indicative of an AF event. The CLV distributioncan be determined during a period when the patient is free of AT, suchas in a sinus rhythm, using population-based or patient historical cyclelengths or cardiac cycles. Similarly, the second comparator circuit 244can compare the HS metric to a population-based or a patient-specificdistribution of ∥S4∥ to determine a second likelihood value of the ∥S4∥value indicative of an AF event. The ∥S4∥ distribution can be determinedwhen the patient is free of AT using population-based or patienthistorical HS data. The blending circuit 246 can generate a compositelikelihood using the first and second likelihood values, and detect theAF event if the composite likelihood meets a specified criterion.

In an example, the cardiac electrical signal metric generator circuit212 can generate a plurality of CLV values using a plurality of cardiaccycles. The HS metric generator circuit 222 can detect S4 heart soundwithin the plurality of cardiac cycle, and generate the S4 intensityindicator for the detected S4 heart sound. The first comparator circuit242 can include a first counter circuit to determine a first relativenumber (N_(CLV)) of the plurality of CLV values that exceed a CLVthreshold (CLV_(TH)) The second comparator circuit 244 can include asecond counter circuit to determine a second relative number (N_(S4)) ofthe cardiac cycles within which a S4 heart sound is detected and the S4intensity exceeds the S4 intensity threshold ∥S4∥_(TH). Examples of therelative numbers N_(CLV) and N_(S4) can include respective ratio,fraction, or percentage, among others. The blending circuit 246 cangenerate a composite score using the first relative number N_(CLV) andthe second relative number N_(S4), and detect the AF event if thecomposite score meets a specified criterion. In an example, the N_(CLV)can represent percentage of the plurality of cardiac cycles satisfyingCLV>CLV_(TH), and N_(S4) can represent percentage of the plurality ofcardiac cycles satisfying ∥S4∥>∥S4∥_(TH). The composite score can becomputed as difference N_(CLV)-N_(S4). Because a larger N_(CLV) mayindicate higher likelihood of occurrence of an AF event, and a largerN_(S4) may indicate stronger evidence of forceful atrial contraction andthus lower likelihood of occurrence of an AF event, the difference(N_(CLV)-N_(S4)) can represent cumulative likelihood of occurrence of anAF event. In an example, the AT detector circuit 240 can detect an AFevent if N_(CLV)-N_(S4) exceeds a specified detection threshold. Otherrelative measures between N_(CLV) and N_(S4), such as weighteddifference, can also be used.

In an example, detection of atrial kick (such as ∥S4∥) can be used toscreen and select cardiac cycles for use in determining the CLV. Thesecond comparator circuit 244 can include a beat selector circuit,coupled to the HS component detector circuit 222, that can select, froma plurality of cardiac cycles used by the HS metric generator circuit222 for detecting S4 heart sound, a subset of cardiac cycles each havinga non-detection of S4 heart sound within the corresponding cardiaccycle, or the intensity of the detected S4 heart sound falling below thethreshold ∥S4∥_(TH). The selected cardiac cycles thus represent timeintervals free of forceful atrial kick, an indication of presence of anAF event. The cardiac electrical signal metric generator circuit 212 canuse only the selected subset of the cardiac cycles to computed CLVvalues. The AT detector circuit 240 can detect the AF event if the CLVvalue exceeds a CLV threshold (CLV_(TH)). In another example, the beatselector circuit can select the subset of cardiac cycles using both theS4 heart sounds and atrial electrical activation, such as when there isno detection of S4 heart sound or ∥S4∥<∥S4∥_(TH), and there is nodetected atrial electrical activation (e.g., no detectable P waves fromthe ECG). The beat selector circuit can alternatively be coupled to thecardiac electrical signal metric generator circuit 212, and can selectfrom a plurality of cardiac cycles a subset of cardiac cyclescorresponding to the CLV exceeding CLV_(TH). The HS component detectorcircuit 222 can detect S4 heart sounds within the selected subset of thecardiac cycles and generate a S4 detection status. The AT detectorcircuit 240 can detect the AF event if the S4 detection status indicatesnon-detection of S4 heart sound within the selected subset of thecardiac cycles, or the S4 intensity indicator falling below the S4intensity threshold ∥S4∥_(TH).

In some examples, detection of atrial kick or atrial electricalactivation can be used to determine a CLV threshold (CLV_(TH)). Thecardiac electrical signal metric generator circuit 212 can detect fromthe cardiac electrical signal the atrial electrical activation (such asP waves from the ECG signal or atrial sensing events from atrial EGM),and generate cardiac electrical signal metric of CLV using the CL or theHR. The AT detector circuit 240 can detect the AF event if the CLV valueexceeds a CLV threshold (CLV_(TH)). Different values of the thresholdCLV_(TH) can be determined based on the detected atrial electricalactivation (e.g., P waves or atrial sensing events) and the atrial kickindicator (e.g., detected S4 heart sound such that ∥S4∥>∥S4 ∥_(TH)). Inan example, a first CLV threshold (CLV_(TH)) can be determined inresponse to both the following conditions are met: (1) the atrial kickindicator of ∥S4∥>∥S4∥_(TH); and (2) the detection of atrial electricalactivation. A second threshold (CLV_(TH2)) can be generated in responseto either, but not both, of the above conditions (1) or (2) is met. Athird threshold (CLV_(TH3)) can be generated in response to neither thecondition (1) nor the condition (2) is met. In an example, CLV_(TH1) canbe greater than CLV_(TH2). In another example, CLV_(TH2) can be greaterthan CLV_(TH3). Detections of both a S4 heart sound with intensity∥S4∥>∥S4∥_(TH) and atrial electrical action (e.g., detection of P waves)may provide stronger evidence of non-occurrence of AF event than if onlyone, but not both, of a S4 heart sound and atrial electrical activationare detected. Thus, a larger threshold value CLV_(TH)(CLV_(TH1)>CLV_(TH2)) may avoid false positive detection of AF event. Inan example, CLV_(TH1) can be set to a positive infinity, whichequivalently allows the AT detector circuit 240 to detect an AF event aslong as there are evidence of atrial electrical activation and strongatrial kick (∥S4∥>∥S4∥_(TH)). A non-detection of S4 (or ∥S4∥<∥S4∥_(TH))along with non-detectable atrial electrical activation (or intensity ofatrial activation falling below a threshold) may be a strong indicatorof presence of an AF event. Thus, a smaller CLV_(TH3)(CLV_(TH3)<CLV_(TH2)) may avoid missing a detection of an AF event.100711 in some examples, atrial kick indicator may provide differentlevels of evidence about occurrence of an AF event than a detection ofatrial electrical activation. For example, based on population data,empirical knowledge, or signal quality (such as a signal noise ratio,SNR), an S4 heart sound with ∥S4∥>∥S4∥_(TH) may indicate a higherlikelihood of occurrence of an AF event than a detection of P waves fromthe ECG or atrial sensing events from the atrial EGM. The AT detectorcircuit 240 can determine a first CLV threshold (CLV_(TH1)) in responseto the detection of ∥S4∥>∥S4∥_(TH), a second CLV threshold (CLV_(TH2))in response to the detection of atrial electrical activation, or a thirdCLV threshold (CLV_(TH3)) in response to neither a detection of S4 heartsound nor a detection of atrial electrical activation. As previouslydiscussed, non-detection of S4 coupled along with no detectable atrialelectrical activation may strongly suggest occurrence of an AF event.Thus, the corresponding threshold CLV_(TH3) can be smaller(CLV_(TH3)<CLV_(TH1) and CLV_(TH3)<CLV_(TH2)) to avoid missing adetection of an AF event. Between CLV_(TH1) and CLV_(TH2), if it isdetermined from population data or empirical knowledge that presence ofS4 is more predictive of non-occurrence of AF, or if S4 has a highersignal quality (e.g., a higher SNR) than that of the P waves or atrialsensing events, then CLV_(TH1) can be greater than CLV_(TH2).Conversely, if the detection of P waves or atrial sensing events is morepredictive of non-occurrence of AF, or if the P waves or the atrial EGMhas a higher SNR than the S4 heart sound, then CLV_(TH1) can be smallerthan CLV_(TH2).

The controller circuit 250 can receive external programming input fromthe user interface unit 260 to control the operations of the cardiacelectrical signal sensor circuit 210, the HS sensor circuit 220, the ATdetector circuit 240, and the data flow and instructions between thesecomponents. The user interface unit 260 can include a display thatpresents programming options to the user and receive system user'sprogramming input. In an example, at least a portion of the userinterface circuit 260, such as the display and user input control, canbe implemented in the external system 120.

The HS-based AT detection circuit 200 can optionally include a therapydelivery circuit that can provide and deliver therapy to the patient inresponse to detection of the AF event, or to withhold the therapy to thepatient if the AF event is no longer detected. The therapy can includeone or more of a cardiac stimulation therapy, a cardiac ablationtherapy, a neurostimulation therapy, or pharmacological therapy, amongother therapy modalities. In an example, the cardiac stimulation therapycan be in a form of electrostimulation to a target tissue inside or onthe heart, including an endocardium or an epicedium of an atrium or aventricle. The electrostimulation can be delivered via one or more ofthe leads 108A-C or the can 112. Examples of electrostimulation therapycan include ventricular rate regularization pacing, atrialanti-tachycardia pacing, atrial cardioversion therapy, or atrialdefibrillation therapy.

FIG. 3 illustrates generally an example of an AT detection circuit 300,which can be an embodiment of the HS-based AT detection circuit 200. TheAT detection circuit 300 can include one or more of a physical activitysensor circuit 310, a posture sensor circuit 320, and an AT detectorcircuit 340. The AT detection circuit 300 can optionally include anarrhythmia classifier circuit 350.

The AT detector circuit 340 can be an embodiment of the AT detectorcircuit 240, and can be implemented as a part of a microprocessorcircuit in the CRM system 100. The microprocessor circuit can be adedicated processor or general purpose processor that can receive andexecute a set of instructions of performing the functions, methods, ortechniques described herein.

The physical activity sensor circuit 310 can be configured to detect aphysical activity or exertion level of the patient. The activity sensorcan be an implantable, wearable, or otherwise ambulatory sensor that isexternal to the patient or implanted inside the body. The activitysensor can be included in at least one part of an implantable system,such as an implantable device, or a lead coupled to the implantabledevice. In an example, the activity sensor can include a single-axis ormulti-axis accelerometer configured to sense an acceleration signal ofat least a portion of the subject's body. The strength of theacceleration signal can be indicative of the physical activity level. Inanother example, the activity sensor can include a respiratory sensorconfigured to measure respiratory parameters correlative or indicativeof respiratory exchange, i.e., oxygen uptake and carbon dioxide output.Examples of the respiratory parameters can include respiration rate,tidal volume, minute ventilation, peak or trough of a respirationsignal, or other indicators of respiration depth; descriptors ofrespiration pattern such as apnea index indicating the frequency ofsleep apnea, hypopnea index indicating the frequency of sleep hypopnea,apnea-hypopnea index (AHI) indicating the frequency of or sleep hypopneaevents, or a rapid shallow breathing index (RSBI) computed as a ratio ofrespiratory frequency (number of breaths per minutes) to tidal volume,among other respiratory parameters.

The posture sensor circuit 320 can be configured to detect a posture orposition of the patient. Examples of the posture sensor can include atilt switch, a single axis accelerometer, or a multi-axis accelerometer,among others. The posture sensor can be disposed external to the body orimplanted inside the body. Posture can be represented by, for example, atilt angle. In another example, patient posture or physical activityinformation can be derived from thoracic impedance information, such asby clustering the thoracic impedance information, as described by Thakuret al in U.S. Patent Application No. 61/423,128, entitled “POSTUREDETECTION USING THORACIC IMPEDANCE”, which is herein incorporated byreference in its entirety.

The AT detector circuit 340 can detect an AT event, such as an AF event,using signal metrics selected based on information about the patientphysical activity level provided by the physical activity sensor circuit310, or information about patient position or posture provided by theposture sensor circuit 320. Similar to the AT detector circuit 240, theAT detector circuit 340 can include a first comparator circuit 242 thatcan produce an atrial rhythm indicator such as by comparing the CLVvalues to a CLV threshold (CLV_(TH)), and a second comparator circuit244 that can produce an atrial kick indicator such as such as bycomparing a S4 heart sound intensity to a specified criterion.

The blending circuit 346 can include a signal metric selector circuit347 coupled to the first and second comparator circuits and one or bothof the physical activity sensor circuit 310 or a posture sensor circuit320. In an example, the blending circuit 346 can select one of thedetected atrial electrical activation (such as provided by the firstcomparator circuit 242) or the detected S4 heart sounds (such asprovided by the second comparator circuit 244) for use in detecting theAF event based on information about the patient's activity or exertionlevel such as provided by the physical activity sensor circuit 310. Thepresent inventors have recognized that a HS sensor may be moresusceptible to noise or interference such as motion artifacts, thusbecomes less reliable when the patent is physically active (e.g., duringphysical exercise) than when the patient is less active (e.g., during arest or sleep state). By contrast, cardiac electrical signals, such asthe ECG or the EGMs, may be less susceptible to motion artifacts. Thesignal metric selector circuit 347 can select the detected atrialelectrical activation (e.g., P waves from the ECG or atrial sensingevents from the atrial EGM) or an atrial rhythm indicator e.g., the CLVcalculated using the HRs or (is obtained from the ECG or the EGM) if thepatient's physical activity level exceeds a specified activity thresholdindicating the patient being physically active. The signal metricselector circuit 347 can select S4 intensity, either alone or togetherwith the atrial electrical activation or the atrial rhythm indicator ifthe physical activity level falls below the specified activity thresholdindicating the patient being physically inactive, resting or sleeping.In another example, the signal metric selector circuit 347 can selectthe detected atrial electrical activation or the atrial rhythm indicatorin response to the posture sensor circuit 320 detecting a first posture,or select S4 intensity if the posture sensor circuit 32.0 detecting asecond posture different from the first posture. By way of non-limitingexample, the first posture can include an upright or standing positionor posture, and the second posture can include a recumbent, supine, orlying down position or posture.

Additionally or alternatively, the signal metric selector circuit 347can include a signal quality analyzer circuit coupled to the posturesensor circuit 320. The signal quality analyzer can compute a firstsignal quality indicator of the detected. atrial electrical activationoccurring during the detected posture, and a second signal qualityindicator of the detected S4 heart sound occurring during the detectedposture. The first signal quality indicator can include a signal tonoise ratio of the detected atrial electrical activation (SNR_(E))during the detected posture, and a second signal quality indicatorincludes a signal to noise ratio of the detected S4 heart sound(SNR_(S4)) during the detected posture. The signal metric selectorcircuit 347 can select the detected atrial electrical activation if thefirst signal quality indicator is greater than the second signal qualityindicator by a specified margin, or select the S4 heart sound if thesecond signal quality is great than the first signal quality indicatorby a specified margin.

The AF onset detector 348, coupled to the signal metric selector circuit347, can use the selected signal metric to detect the AF event, such asin response to non-detection of P waves, CLV exceeding the thresholdCLV_(TH), or non-detection of S4 heart sound or the S4 intensity fallingbelow the threshold ∥S4∥_(TH).

The arrhythmia classifier circuit 350 can be coupled to AT detectorcircuit 340, and the first and second signal metric generator circuits242 and 244 or the memory circuit 230, and configured to classify thedetected AT event as one of an AF event or an atrial flutter (AFL)event. An AFL occurs when an abnormal conduction circuit develops insidethe atrium and drives the atrial rate excessively fast, such asapproximately 250-300 beats per minute. Compared to typicallydiscoordinated atrial activity during AF, electrical activity in theatria during AFL may be coordinated.

The arrhythmia classifier circuit 350 can determine a composite metricusing the cardiac electrical signal metric and the HS metric. Thearrhythmia classifier circuit 350 can confirm the detected AT event asan AF event if the composite metric meets a first specified criterion,or classify the detected AT event as an AFL event if the compositemetric meets a second specified criterion. In an example, the arrhythmiaclassifier circuit 350 can include a comparator circuit 351 that cangenerate an atria-ventricular (A-V) conduction pattern representing acorrespondence between atrial and ventricular activities. The A-Vconduction pattern can include a ratio (AVR) of a number of S4 heartsounds to a number of ventricular activations during a specified numberof cardiac cycles. For example, the AVR can be represented by n:1 A-Vconduction indicating a correspondence of n atrial contractions (e.g., nS4 heart sounds) for every one ventricular activation (e.g., an R waveor a QRS complex in a ECG, or a ventricular sensing event in an EGM).The AVR can be represented by n:m A-V conduction indicating acorrespondence of n atrial contractions (e.g., n S4 heart sounds) forevery in ventricular activations. The arrhythmia classifier circuit 350can determine a composite metric including a variability measure(AVR_(var)) of the AVR, such as a range, variance, standard deviation,or other statistics of spreadness that indicate consistency of the AVconduction pattern over time. The arrhythmia classifier circuit 350 canconfirm the detected AT event as an AF event if the AVR_(var) exceeds aspecified threshold, which indicates lack of a consistent A-V conductionpattern. The arrhythmia classifier circuit 350 can classify the detectedAT event as an AFL event if the AVR_(var) falls below the specifiedthreshold, which indicates a consistent A-V conduction pattern.

In an example, the arrhythmia classifier circuit 350 can include a timercircuit 352 that can generate an atrio-ventricular (A-V) conductiondelay, which can include a time interval between the detected S4 heartsound and the ventricular activation (e.g., R waves, QRS complexes in anECG, or ventricular sensed events in an EGM) within the same cardiaccycle. A consistent and stable atrio-ventricular interval (AVI) mayindicate occurrence of an AFL event, while an inconsistent and variableAVI may be a characteristic of an AF event. The arrhythmia classifiercircuit 350 can determine a composite metric including a variabilitymeasure (AVI_(var)) of the AVI, such as a range, variance, standarddeviation, or other statistics of spreadness that indicate consistencyof the AV conduction delay over time. The arrhythmia classifier circuit350 can confirm the detected AT event as an AF event if the AV_(var)exceeds a specified threshold, or classify the detected AT event as anAFL event if the AVI_(var) falls below the specified threshold.

FIG. 4 illustrates generally an example of a method 400 for detecting anAT event in a patient. An example of the AT event is an atrialfibrillation (AF) event. The method 400 can be implemented and operatein an ambulatory medical device or in a remote patient managementsystem. In an example, the IMD 110 or the external system 120, includingits various examples discussed in this document, can be programmed toperform method 400, including its various examples discussed in thisdocument.

The method 400 can begin at 410 where a cardiac electrical signal can besensed, such as by using one or more implantable, wearable, or otherwiseambulatory cardiac activity sensors configured to sense cardiacelectrical activity. Examples of the cardiac electrical signal caninclude surface or subcutaneous electrocardiogram (ECG), or one or moreelectrocardiograms (EGMs) sensed by using electrodes on one or more ofthe leads 108A-C or the can 112. Atrial depolarization events, such as Pwaves sensed from an ECG or atrial sensing events from an atrial EGM,and ventricular depolarization events, such as R waves sensed from anECG or ventricular sensing events from a ventricular EGM, can be sensed.

At 420, one or more cardiac electrical signal metric can be generated.In one example, the cardiac electrical signal metric can include cyclelength variability (CLV) or a heart rate variability (HRV) valueindicative of variability of the CL or HR. The CLR or HRV can include aspreadness measure computed using a plurality of HRs or CLs over aspecified period of time. In an example, the cardiac electrical signalmetric can include a presence or intensity of the atrialdepolarizations, such as a P wave or atrial sensing events.

At 430, a heart sound (HS) signal can be sensed, such as by using one ormore physiologic sensors that can sense acoustic or mechanical vibrationof a heart. Examples of the sensors for sensing HS can include anaccelerometer, an acoustic sensor such as a microphone, piezo-basedsensor, or other vibrational or acoustic sensors can also be used tosense the HS signal.

At 440, at least one HS metric can be generated from the sensed HSsignal. The HS metric can be indicative or correlative of atrialmechanical contraction, which can include a S4 heart sound metric. TheS4 heart sound may generally be associated with atrial contraction.Regular and forceful atrial contraction may be diminished during an AFepisode. A detection of forceful S4 may be an evidence of absence of AF.The S4 heart sound can be detected using a specified detection windowwith reference to a physiologic event such as R wave, Q wave, or QRScomplexes, or other HS components such as S1 or S3 heart sounds. The S4heart sound can additionally or alternatively be detected using a S4template matching method.

The S4 metric can include a detection status of S4 heart sound, andtemporal, statistical, or morphological features of the detected S4heart sound. Examples of the intensity of a HS component can includeamplitude of a detected HS component in a time-domain HS signal, atransformed HS signal such as integrated HS energy signal, or in afrequency-domain HS signal such as the peak value of the power spectraldensity, or peak value of a generic measurement within the respective HSdetection window, such as peak envelop signal or root-mean-squared valueof the portion of the HS signal within the HS detection window.

At 450, the cardiac electrical signal metric and the HS metric can beused to detect an AT event, such as an AF event, such as by using the ATdetector circuits 240 or 340 as illustrated in FIGS. 2-3, or amicroprocessor that can be configured to receive and execute a set ofinstructions of performing the functions, methods, or techniquesdescribed herein. In an example, the cardiac electrical signal metrics,including one or more of a cycle length variability (CLV) of cyclelength (CL) or HR computed from the cardiac electrical signal, or adetection of atrial electrical activation (e.g., P waves in a ECG), canbe generated. HS metrics, including one or more of a S4 detection statusindicating whether a S4 heart sound is detected within the cardiaccycle, or a S4 intensity indicator of the detected S4 heart sound, canalso be generated. Detecting the AF event can include comparing the CLVto a CLV threshold (CLV_(TH)), and comparing the S4 intensity (if S4 isdetected) to a S4 intensity threshold (∥S4∥_(TH)). An AF is deemeddetected if (1) the CLV value exceeds a CLV threshold (CLV_(TH)), and(2) the S4 detection status indicates a non-detection of S4 heart sound,or the S4 intensity indicator falls below a S4 intensity threshold(∥S4∥_(TH)). In an example, the CLV_(TH) can be set a relatively lowlevel such that CLV can be sensitive to cycle length variations producedby AF or other physiologic or non-physiological conditions. The∥S4∥_(TH) can be selected such that the atrial kick indicator, such as anon-detection of S4 or a below-the-threshold S4 intensity can bespecific to an AF event. Other examples of detecting AF are discussedbelow, such as with reference to FIGS. 5-8.

The method 400 can additionally include a step 460 of classifying thedetected AT event as one of an AF event or an atrial flutter (AFL)event, such as by using the arrhythmia classifier circuit 350 or anyvariants thereof. A composite metric can be determined using the cardiacelectrical signal metric and the HS metric. In an example, the compositemetric can include an atrio-ventricular (A-V) conduction patternrepresenting a pattern of correspondence between atrial and ventricularactivities. The A-V conduction pattern can include a ratio (AVR) of anumber of S4 heart sounds to a number of ventricular activations duringa specified number of cardiac cycles. In another example, the compositemetric can include an A-V conduction delay, such as a time interval(AVI) between the detected S4 heart sound and the ventricular activationwithin the same cardiac cycle. A variability measure (AVR_(var)) of theAVR, or a variability measure (AVI_(var)) of the AVI, can be computed,which respectively represents consistency of the atrio-ventricularconduction pattern or stability of the atrio-ventricular interval. An AFevent can be confirmed if the AVR_(var) or the AVI_(var) exceedsrespective thresholds, indicating a consistent atrio-ventricularconduction pattern or a stable atrio-ventricular interval.Alternatively, the detected AT event can be classified as an AFL eventif the AVR_(var) or the AVI_(var) falls below the respective thresholds,indicating an inconsistent atrio-ventricular conduction pattern or anunstable atrio-ventricular interval.

The method 400 can include a step of generating an alert of a detectionof an AF event or AFL event. The method 400 can include a step ofdelivering a specified therapy to the patient, such as by using atherapy circuit in response to a detection of the AF or AFL event, or towithhold the therapy in response to a detection of termination of the AFor the AFL event. The therapy can include one or more of a cardiacstimulation therapy, a cardiac ablation therapy, a neurostimulationtherapy, or pharmacological therapy. In an example, the cardiacstimulation therapy can be in a form of electrostimulation to a targetinside or on the heart, including an endocardium or an epicedium of anatrium or a ventricle.

FIGS. 5A-B illustrate generally examples of methods for detecting an AFevent using a cardiac electrical signal metric and a HS metric. FIG. 5Aillustrates a method 550A, and FIG. 5B illustrates a method 550B, eachof which can be an embodiment of the step 450 of the method 400 asillustrated in FIG. 4.

The method 550A includes a step at 551for determining, from a pluralityof CLV values computed over a plurality of cardiac cycles, a firstsubset of CLV values each exceeding the CLV_(TH). A first relativenumber (N_(CLV)) can also be determined, such as a ratio, a fraction, ora percentage of the number of CLV values in the first subset to thetotal number of the plurality of the CLV values. At 552, from theplurality of cardiac cycles used for computing the CLV values, a secondsubset of cardiac cycles can be determined, where each cardiac cycle inthe second subset includes a detected S4 heart sound with correspondingS4 intensity exceeding the threshold ∥S4∥_(TH). A second relative number(N_(S4)) can also be determined, such as a ratio, a fraction, or apercentage of the number of cardiac cycles in the second subset to thetotal number of the plurality of the CLV values. In an example, theN_(CLV) can represent percentage of the plurality of cardiac cyclessatisfying CLV>CLV_(TH), and N_(S4) can represent percentage of theplurality of cardiac cycles satisfying ∥S4∥>∥S4∥_(TH). At 553, acomposite score can be generated using the first and second relativenumber, such as a difference N_(CLV)-N_(S4). A larger N_(CLV) indicateshigher likelihood of occurrence of an AF event, and a larger N_(S4) isan evidence of forceful atrial contraction and thus lower likelihood ofoccurrence of an AF event. As such, the difference (N_(CLV)-N_(S4)) canbe used as a cumulative evidence of occurrence of an AF event. At 554,the composite score can be compared against a criterion, such as athreshold value. An AF event is deemed detected at 555 if the compositescore exceeds the threshold. If the composite score does not exceed thethreshold, then at 556 no AF event is deemed detected; and the detectionprocess can be continued by sensing cardiac electrical signals at 410.

The method 550B includes selecting, from a plurality of cardiac cyclesfor detecting S4 heart sound, a subset of cardiac cycles each having theS4 detection status indicating non-detection of S4 heart sound withinthe corresponding cardiac cycle, or the S4 intensity indicator of thedetected S4 heart sounds falling below the ∥S4∥_(TH), that is,∥S4∥<∥S4∥_(TH). The selected cardiac cycles thus represent timeintervals free of forceful atrial kick, an indication of presence of AF.At 562, only the selected subset of the cardiac cycles are used tocompute a CLV value, such as a variance, a standard deviation, or otherstatistical measure of spreadness of the selected cardiac cycles. At563, the CLV can be compared to a threshold CLV_(TH). If the CLV valueexceeds the threshold CLV_(TH), an AF event is deemed detected at 564.If the CLV value falls below the CLV_(TH), then no AF event is deemeddetected; and the detection process can be continued by sensing cardiacelectrical signals at 410.

FIG. 6 illustrates generally an example of a method 650 for detecting anAF event using a cardiac electrical signal, a HS signal, and informationabout physical activity level of the patient. The method 650 can be anembodiment of the step 450 of the method 400 as illustrated in FIG. 4,and can be programmed to and executed by the AT detection circuit 300.The method 650 can include a step of detecting a physical activity orexertion level of the patient, such as by using a single-axis ormulti-axis accelerometer or an impedance signal indicative ofrespiratory exchange. The strength of the acceleration signal, or therespiration rate, tidal volume, or minute ventilation, apnea-hypopneaindex (AHI), a rapid shallow breathing index (RSBI), among otherparameters derived from the respiration signal, can indicate the levelof physical activity or exertion of the patient.

At 652, the detected physical activity or exertion level can be comparedto a threshold. If the physical activity level exceeds the threshold,such as when the patient is physically active or during exercise, thenthe detected cardiac electrical activation (such as the P waves or theCLV values) can be used for detecting AF event at 653. For example, asillustrated in FIG. 6, if P waves are detected or the CLV value fallsbelow the threshold CLV_(TH), no AF event is deemed detected at 656.However, if at 653 the P waves are not detected, and if the CLV isgreater than the CLV_(TH), an AF event is deemed detected at 655. If at652 the patient's physical activity or exertion level is less than theactivity threshold, such as when the patient is physically inactive orin a state of rest or sleep, the HS metric such as the S4 heart soundmetric can be used to detect the AF event. At 654, the S4 intensityindicator can be compared to the threshold ∥S4∥_(TH). If the S4intensity exceeds the ∥S4∥_(TH), forceful atrial kick is likely presentand no AF event is deemed detected at 656. However, if the S4 intensityfalls below the ∥S4∥_(TH), or no S4 heart sound is detected, then an AFevent is deemed detected at 655. When no AF event is detected eitheraccording to the electrical signal metrics or the HS metric, thedetection process can be continued by sensing cardiac electrical signalsat 410.

FIG. 7 illustrates generally an example of a method 750 for detecting anAF event using a cardiac electrical signal, a HS signal, and postureinformation. The method 750 can be an embodiment of the step 450 of themethod 400 as illustrated in FIG. 4. The method 750 can include a step751 of detecting the patient's posture, such as by using a tilt switch,a single axis accelerometer, or a multi-axis accelerometer, thoracicimpedance sensors, among others. At 752, respective signal qualityindicators of the detected atrial electrical activation and the S4 heartsound can be determined, such as a first signal-to-noise ratio (SNR_(E))of the detected atrial electrical activation occurring during thedetected posture, and a second signal-to-noise ratio (SNR_(S4)) of thedetected S4 heart sound occurring during the detected posture. The twosignal quality indicators can be compared at 753. If SNR_(E) is greaterthan SNR_(S4), the electrical signal metrics are deemed more reliablethan S4 metric, and the cardiac electrical activation (such as the Pwaves or the CLV values) can be used for detecting AF event at 754.Similar to step 653 of FIG. 6, an AF event is deemed not detected at 757if the P wave is detected or the CLV<CLV_(TH), or otherwise deemeddetected at 756. If at 753 the SNR_(E) is less than SNR_(S4), the HSmetric is deemed more reliable than cardiac electrical signal metrics,and the S4 intensity can be used to detect the AF event at 755. An AFevent is deemed not detected at if ∥S4∥>∥S4∥_(TH), or otherwise deemeddetected at 756. When no AF event is detected either according to theelectrical signal metrics or the HS metric, the detection process can becontinued by sensing cardiac electrical signals at 410.

FIG. 8 illustrates generally an example of a method 850 for detecting anAF event using a cardiac electrical signal and a HS signal. The method850 detects an AF event if the CLV value exceeds a CLV threshold(CLV_(TH)), where the threshold CLV_(TH) can be determined using atleast one of the detected atrial electrical activation (e.g., P waves oratrial sensing events) and the atrial kick indicator (e.g., a detectedS4 with intensity exceeding a threshold ∥S4∥_(TH)). If the detected S4intensity exceeds the threshold value ∥S4∥_(TH) and the P waves aredetected at 851, then a first CLV threshold (CLV_(TH1)) can bedetermined at 853. If only one, but not both, of the atrial electricalactivation and atrial kick indicator are present, that is, either the Pwaves are detected or ∥S4∥>∥S4∥_(TH) at 852, then a second threshold(CLV_(TH2)) can be generated at 854. If there is neither a detection ofS4 heart sound (or the detected S4 intensity falls below the threshold∥S4 ∥_(TH)) nor a detection of atrial electrical activation (e.g., no Pwaves detected), then a third threshold (CLV_(TH3)) can be generated at855. A detection of ∥S4∥>∥S4∥_(TH) along with the detection of P wavesprovides a stronger evidence of presence of an AF episode than either∥S4∥>∥S4∥_(TH) or the detection of P waves alone, and a non-detection ofS4 heart sound along with a non-detection of P waves is highlypredictive of presence of an AF episode. The CLV thresholds can thus bedetermined such that CLV_(TH1)>CLV_(TH2)>CLV_(TH2) to avoid falsepositive detection of AF event (with a large CLV_(TH1)) or to avoidmissing a detection of a true AF event (with a small CLV_(TH3)). In someexamples, when the condition at 852 is met, atrial kick indicator mayprovide different levels of evidence of occurrence of AF than adetection of atrial electrical activation, and different CLV thresholdvalues may be determined in accordance with the detection of∥S4∥>∥S4∥_(TH) or the detection of P waves, instead of a commonthreshold CLV_(TH2). For example, based on population data, empiricalknowledge, or signal quality (such as a signal noise ratio), if∥S4∥>∥S4∥_(TH) is found to more predictive of an occurrence of an AFevent than detection of P waves, the CLV threshold (CLV_(TH2a))corresponding to ∥S4∥>∥S4∥_(TH) (but no P wave detection) can be higherthan the CLV threshold (CLV_(TH2b)) corresponding to P wave detection(but no detection of S4 or ∥S4∥<∥S4∥_(TH)). The CLV threshold valuesunder different combinations of atrial electrical activation and atrialkick indicator can be related asCLV_(TH)>CLV_(TH2a)>CLV_(TH2b)>CLV_(TH3).

At 856, the CLV can be compared to the threshold CLV_(TH). If the CLVvalue exceeds a CLV threshold CLV_(TH), an AF event is deemed detectedat 564. If the CLV value falls below the CLV_(TH), then no AF event isdeemed detected; and the detection process can be continued by sensingcardiac electrical signals at 410,

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments in which theinvention can be practiced. These embodiments are also referred toherein as “examples.” Such examples can include elements in addition tothose shown or described. However, the present inventors alsocontemplate examples in which only those elements shown or described areprovided. Moreover, the present inventors also contemplate examplesusing any combination or permutation of those elements shown ordescribed (or one or more aspects thereof), either with respect to aparticular example (or one or more aspects thereof), or with respect toother examples one or more aspects thereof) shown or described herein.

In the event of inconsistent usages between this document and anydocuments so incorporated by reference, the usage in this documentcontrols.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In this document, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, composition, formulation, or process that includes elements inaddition to those listed after such a term in a claim are still deemedto fall within the scope of that claim. Moreover, in the followingclaims, the terms “first,” “second,” and “third,” etc. are used merelyas labels, and are not intended to impose numerical requirements ontheir objects.

Method examples described herein can be machine or computer-implementedat least in part. Some examples can include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods can include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code can include computer readable instructions forperforming various methods. The code may form portions of computerprogram products. Further, in an example, the code can be tangiblystored on one or more volatile, non-transitory, or non-volatile tangiblecomputer-readable media, such as during execution or at other times.Examples of these tangible computer-readable media can include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e,g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAMS), read onlymemories (ROMs), and the like.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or me or moreaspects thereof) may be used in combination with each other. Otherembodiments can be used, such as by one of ordinary skill in the artupon reviewing the above description. The Abstract is provided to complywith 37 C.F.R. § 1.72(b), to allow the reader to quickly ascertain thenature of the technical disclosure. It is submitted with theunderstanding that it will not be used to interpret or limit the scopeor meaning of the claims. Also, in the above Detailed Description,various features may be grouped together to streamline the disclosure.This should not be interpreted as intending that an unclaimed disclosedfeature is essential to any claim. Rather, inventive subject matter maylie in less than all features of a particular disclosed embodiment.Thus, the following claims are hereby incorporated into the DetailedDescription as examples or embodiments, with each claim standing on itsown as a separate embodiment, and it is contemplated that suchembodiments can be combined with each other in various combinations orpermutations. The scope of the invention should be determined withreference to the appended claims, along with the full scope ofequivalents to which such claims are entitled.

What is claimed is:
 1. A system, comprising: a first signal metricgenerator circuit configured to generate a cardiac electrical signalmetric indicative of beat-to-beat cardiac activity from a patient; asecond signal metric generator circuit configured to generate an S4heart sound metric using heart sound information of the patient; and anatrial tachyarrhythmia (AT) detector circuit configured to detect an ATevent of the patient using the generated cardiac electrical signalmetric and the S4 heart sound metric.
 2. The system of claim 1, whereinthe cardiac electrical signal metric includes a ventricular cycle lengthor a ventricular heart rate.
 3. The system of claim 2, wherein thecardiac electrical signal metric includes a beat-to-beat ventricularcycle length difference or a beat-to-beat ventricular heart ratedifference.
 4. The system of claim 2, wherein the cardiac electricalsignal metric includes a statistic of multiple measurements of theventricular cycle length or a static of multiple measurements of theventricular heart rate.
 5. The system of claim 1, wherein the S4 heartsound metric includes an indication of presence or absence of S4 heartsound within a cardiac cycle, and the AT detector circuit is configuredto detect an AT event in response to (1) the generated cardiacelectrical signal metric satisfying a first condition, and (2) anindication of absence of S4 heart sound.
 6. The system of claim 5,wherein the second signal metric generator circuit is configured togenerate an S4 morphology matching score with reference to an S4template, and to determine a presence of S4 heart sound if the S4morphology matching score exceeds an S4 metric threshold, or an absenceof S4 heart sound if the S4 morphology matching score falls below the S4metric threshold.
 7. The system of claim 5, wherein the generatedcardiac electrical signal metric includes a beat-to-beat ventricularcycle length difference over multiple cardiac cycles, and wherein the ATdetector circuit is configured to detect an AT event in response to (1)the beat-to-beat ventricular cycle length difference exceeding a cyclelength difference threshold, and (2) an indication of absence of S4heart sound.
 8. The system of claim 5, wherein the AT detector circuitis configured to: determine, over a plurality of cardiac cycles: (1) afirst relative number of cardiac cycles with respective beat-to-beatventricular cycle length differences exceeding a cycle length differencethreshold, and (2) a second relative number of cardiac cycles withrespective S4 heart sound metrics exceeding an S4 metric threshold; anddetect the AT event using the first and second relative numbers.
 9. Thesystem of claim 8, wherein the AT detector circuit is configured todetect the AT event using a relative difference between the firstrelative number and the second relative number.
 10. The system of claim5, comprising a beat selector circuit configured to select, from aplurality of cardiac cycles, a subset of cardiac cycles with respectiveindications of absence of S4 heart sound therewithin, and wherein: thesignal metric generator circuit is configured to compute a beat-to-beatventricular cycle length difference using the selected subset of thecardiac cycles; and the AT detector circuit is configured to detect theAT event in response to the computed beat-to-beat ventricular cyclelength difference exceeding a threshold.
 11. The system of claim 5,comprising a beat selector circuit configured to select, from aplurality of cardiac cycles, a subset of cardiac cycles with respectivebeat-to-beat ventricular cycle length differences exceeding a cyclelength difference threshold, wherein: the second signal metric generatorcircuit is configured to generate an indication of presence or absenceof S4 heart sound within the selected subset of the cardiac cycles; andthe AT detector circuit is configured to detect the AT event in responseto an indication of absence of S4 heart sound within the selected subsetof the cardiac cycles.
 12. The system of claim 5, wherein the ATdetector circuit is configured to determine a cycle length differencethreshold using the determined S4 heart sound metric, and to detect theAT event if the beat-to-beat ventricular cycle length difference exceedsthe determined cycle length difference threshold.
 13. The system ofclaim 1, comprising an arrhythmia classifier circuit configured toclassify the detected AT event as an atrial fibrillation event or anatrial flutter event using the generated cardiac electrical signalmetric and the generated S4 heart sound metric.
 14. A method,comprising: generating, using a first signal generator circuit, acardiac electrical signal metric indicative of beat-to-beat cardiacactivity from a patient; generating, using a second signal metricgenerating circuit, an S4 heart sound metric using heart soundinformation of the patient; and detecting, using an atrialtachyarrhythmia (AT) detector circuit, an AT event of the patient usingthe generated cardiac electrical signal metric and the S4 heart soundmetric.
 15. The method of claim 14, wherein the cardiac electricalsignal metric includes a ventricular cycle length or a ventricular heartrate.
 16. The method of claim 14, wherein the S4 heart sound metricincludes an indication of presence or absence of S4 heart sound within acardiac cycle, and wherein detecting the AT event is in response to (1)the generated cardiac electrical signal metric satisfying a firstcondition, and (2) an indication of absence of S4 heart sound.
 17. Themethod of claim 16, wherein generating the S4 heart sound metricincludes computing an S4 morphology matching score with reference to anS4 template, and determining a presence of S4 heart sound if the S4morphology matching score exceeds an S4 metric threshold, or an absenceof S4 heart sound if the S4 morphology matching score falls below the S4metric threshold.
 18. The method of claim 16, wherein the generatedcardiac electrical signal metric includes a heat-to-heat ventricularcycle length difference over multiple cardiac cycles, and whereindetecting the AT event is in response to (1) the beat-to-beatventricular cycle length difference exceeding a cycle length differencethreshold, and (2) an indication of absence of S4 heart sound.
 19. Themethod of claim 16, comprising: determining a cycle length differencethreshold using the determined S4 heart sound metric; and detecting theAT event in response to the beat-to-beat ventricular cycle lengthdifference exceeding the determined cycle length difference threshold.20. The method of claim 16, comprising: determining, over a plurality ofcardiac cycles: (1) a first relative number of cardiac cycles withrespective beat-to-beat ventricular cycle length differences exceeding acycle length difference threshold, and (2) a second relative number ofcardiac cycles with respective S4 heart sound metrics exceeding an S4metric threshold; and detecting the AT event using a composite score ofthe first and second relative numbers.